Results 1  10
of
4,286
The Stability of Faculty Input Coefficients in Linear
"... *University of California Two linear workload models of the University of California have been developed which can be used to forecast the university's demand for faculty.Both utilize a matrix of faculty input coefficients to transform a vector of student enrqllment projections into a forecas ..."
Abstract
 Add to MetaCart
*University of California Two linear workload models of the University of California have been developed which can be used to forecast the university's demand for faculty.Both utilize a matrix of faculty input coefficients to transform a vector of student enrqllment projections into a
Some Trends on Change in Direct Input Coefficient of China
, 2000
"... In input output analysis direct input coefficient plays a very important role. In order to study the trends on change in direct input coefficient it is necessary to have a timeseries of inputoutput ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
In input output analysis direct input coefficient plays a very important role. In order to study the trends on change in direct input coefficient it is necessary to have a timeseries of inputoutput
Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants
 Review of Economic Studies
, 2002
"... This paper empirically investigates the effects of liberalized trade on plant productivity in the case of Chile. Chile presents an interesting setting to study this relationship since it underwent a massive trade liberalization that significantly exposed its plants to competition from abroad during ..."
Abstract

Cited by 555 (16 self)
 Add to MetaCart
in the estimates of the input coefficients required to construct a productivity measure. I explicitly incorporate plant exit in the estimation to correct for the selection problem induced by liquidated plants. These methodological aspects are important in obtaining a reliable plantlevel productivity measure based
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
Abstract

Cited by 783 (29 self)
 Add to MetaCart
of the weight vector in an associated feature space. The expansion coefficients are found by solving a quadratic programming problem, which we do by carrying out sequential optimization over pairs of input patterns. We also provide a preliminary theoretical analysis of the statistical performance of our
An Efficient Solution to the FivePoint Relative Pose Problem
, 2004
"... An efficient algorithmic solution to the classical fivepoint relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degre ..."
Abstract

Cited by 484 (13 self)
 Add to MetaCart
An efficient algorithmic solution to the classical fivepoint relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth
Deep Neural Networks for Acoustic Modeling in Speech Recognition
"... Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models to determine how well each state of each HMM fits a frame or a short window of frames of coefficients that represents the acoustic input. An alternative ..."
Abstract

Cited by 272 (47 self)
 Add to MetaCart
Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models to determine how well each state of each HMM fits a frame or a short window of frames of coefficients that represents the acoustic input
A SignalProcessing Framework for Inverse Rendering
 In SIGGRAPH 01
, 2001
"... Realism in computergenerated images requires accurate input models for lighting, textures and BRDFs. One of the best ways of obtaining highquality data is through measurements of scene attributes from real photographs by inverse rendering. However, inverse rendering methods have been largely limit ..."
Abstract

Cited by 248 (21 self)
 Add to MetaCart
Realism in computergenerated images requires accurate input models for lighting, textures and BRDFs. One of the best ways of obtaining highquality data is through measurements of scene attributes from real photographs by inverse rendering. However, inverse rendering methods have been largely
Learning Decision Trees using the Fourier Spectrum
, 1991
"... This work gives a polynomial time algorithm for learning decision trees with respect to the uniform distribution. (This algorithm uses membership queries.) The decision tree model that is considered is an extension of the traditional boolean decision tree model that allows linear operations in each ..."
Abstract

Cited by 207 (10 self)
 Add to MetaCart
node (i.e., summation of a subset of the input variables over GF (2)). This paper shows how to learn in polynomial time any function that can be approximated (in norm L 2 ) by a polynomially sparse function (i.e., a function with only polynomially many nonzero Fourier coefficients). The authors
The contribution of publicly provided inputs to states’ economies
 JOURNAL OF REGIONAL SCIENCE
, 1992
"... We specify a regional production function that, in addition to labor and private capital, includes two publicly provided inputs highways and education. We employ a panel data set consisting of annual observations on the 48 contiguous states from 1969 to 1983 to estimate input elasticity coefficient ..."
Abstract

Cited by 111 (2 self)
 Add to MetaCart
coefficients under a specification that allows for differences over time and across tates. We find that both of the publicly provided inputs have a significant and positive effect on output. Our results support the policy conclusion that publicly provided infrastructure is an important element of economic
Image SuperResolution via Sparse Representation
"... This paper presents a new approach to singleimage superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepresented as a sparse linear combination of elements from an appropriately chosen overcomplete dictionary. Inspired by th ..."
Abstract

Cited by 194 (9 self)
 Add to MetaCart
by this observation, we seek a sparse representation for each patch of the lowresolution input, and then use the coefficients of this representation to generate the highresolution output. Theoretical results from compressed sensing suggest that under mild conditions, the sparse representation can be correctly
Results 1  10
of
4,286